نتایج جستجو برای: multiple histogram method

تعداد نتایج: 2285760  

2010
Danni Ai Atsushi Okamoto Yae Kikutani Yoshiyuki Tanaka Xian-Hua Han Yen-Wei Chen

ion In this paper, we describe our first participation for the semantic indexing task at TRECVID 2010 [1]. We focus on extraction multiple low-level feature sets and a fusion method. In our system, six features are extracted for all the predefined concepts from the keyframes, including global features (RGB color histogram, HSV color histogram, edge histogram, Grey Level Co-occurrence Matrix, GI...

2015
Jun Wang Guoqing Wang Ming Li Wenkai Du Wenhui Yu

Based on the Histogram equalization theory, this paper presents a novel concept of histogram to realize the contrast enhancement of hand vein images, avoiding the lost of topological vein structure or importing the fake vein information. Firstly, we propose the concept of gray-level information histogram, the fundamental characteristic of which is that the amplitudes of the components can objec...

Journal: :The Journal of Chemical Physics 1977

Journal: :Computer Physics Communications 2002

2004
Shankar Kumar Djamal Bouzida

The Weighted Histogram Analysis Method (WHAM), an extension of Ferrenberg and Swendsen’s Multiple Histogram Technique, has been applied for the first time on complex biomolecular Hamiltonians. The method is presented here as an extension of the Umbrella Sampling method for free-energy and Potential of Mean Force calculations. This algorithm possesses the following advantages over methods that a...

Journal: :Algorithms 2014
Yung-Tsang Chang Jen-Tse Wang Wang-Hsai Yang

Contrast enhancement plays a fundamental role in image processing. Many histogram-based techniques are widely used for contrast enhancement of given images, due to their simple function and effectiveness. However, the conventional histogram equalization (HE) methods result in excessive contrast enhancement, which causes natural looking and satisfactory results for a variety of low contrast imag...

Journal: :SIAM J. Comput. 2010
Vladimir Braverman Rafail Ostrovsky

In the streaming model, elements arrive sequentially and can be observed only once. Maintaining statistics and aggregates is an important and nontrivial task in this model. These tasks become even more challenging in the sliding windows model, where statistics must be maintained only over the most recent n elements. In their pioneering paper, Datar et al. [SIAM J. Comput., 31 (2002), pp. 1794–1...

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